Publications by authors named "Shu-Zhen Peng"
Article Synopsis
- The study focuses on improving emergency department triage for patients with acute abdominal pain by using machine learning models to identify those who may require urgent surgery more accurately than traditional logistic regression models.
- Researchers analyzed data from 38,214 patients at Zhongnan Hospital over eight years, employing both structured (like vital signs) and unstructured data (like patient complaints) to predict surgical outcomes.
- The results showed that machine learning models, particularly Light GBM, had better predictive performance than the conventional models, with higher accuracy metrics such as the area under the curve (AUC) and improved net reclassification indexes.
